Ontology driven AI and Access Control Systems for Smart Fisheries

dc.contributor.authorChukkapalli, Sai Sree Laya
dc.contributor.authorAziz, Shaik
dc.contributor.authorAlotaibi, Nouran
dc.contributor.authorMittal, Sudip
dc.contributor.authorGupta, Maanak
dc.contributor.authorAbdelsalam, Mahmoud
dc.date.accessioned2021-02-08T16:18:26Z
dc.date.available2021-02-08T16:18:26Z
dc.date.issued2021-04-28
dc.descriptionSAT-CPS '21: Proceedings of the 2021 ACM Workshop on Secure and Trustworthy Cyber-Physical Systems
dc.description.abstractIncreasing number of internet connected devices has paved a path for smarter ecosystems in various sectors such as agriculture, aquaculture, manufacturing, healthcare, etc. Especially, integrating technologies like big data, artificial intelligence (AI), blockchain, etc. with internet connected devices has increased efficiency and productivity. Therefore, fishery farmers have started adopting smart fisheries technologies to better manage their fish farms. Despite their technological advancements smart fisheries are exposed and vulnerable to cyber-attacks that would cause negative impact on the ecosystem both physically and economically. Therefore in this paper, we present a smart fisheries ecosystem where the architecture describes various interactions that happen between internet connected devices. We develop a smart fisheries ontology based on the architecture and implement Attribute Based Access Control System (ABAC) where access to resources of smart fisheries is granted by evaluating the requests. We also discuss how access control decisions are made in multiple use case scenarios of a smart fisheries ecosystem. Furthermore, we elaborate some AI applications that would enhance the smart fisheries ecosystem.en_US
dc.description.urihttps://dl.acm.org/doi/10.1145/3445969.3450429en_US
dc.format.extent10 pagesen_US
dc.genreconference papers and proceedingsen_US
dc.genrepreprints
dc.identifierdoi:10.13016/m24nbt-c6im
dc.identifier.citationSai Sree Laya Chukkapalli, Shaik Aziz, Nouran Alotaibi, Sudip Mittal, Maanak Gupta, and Mahmoud Abdelsalam, Ontology driven AI and Access Control Systems for Smart Fisheries, SAT-CPS '21: Proceedings of the 2021 ACM Workshop on Secure and Trustworthy Cyber-Physical Systems, April 2021, Pages 59–68; https://doi.org/10.1145/3445969.3450429en_US
dc.identifier.urihttp://hdl.handle.net/11603/20969
dc.identifier.urihttps://doi.org/10.1145/3445969.3450429
dc.language.isoen_USen_US
dc.publisherAssociation for Computing Machinery
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.relation.ispartofUMBC Student Collection
dc.relation.ispartofUMBC Faculty Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.subjectsmart fisheriesen_US
dc.subjectontologyen_US
dc.subjectcybersecurityen_US
dc.subjectaccess controlen_US
dc.subjectartificial intelligenceen_US
dc.subjectUMBC Ebiquity Research Group
dc.titleOntology driven AI and Access Control Systems for Smart Fisheriesen_US
dc.typeTexten_US

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